In manufacturing and assembly processes, it is often desirable to measure some or all of an object surface with a high degree of accuracy and generate a map of the overall displacement or “profile” (e.g. height in the physical z-coordinate direction) with respect to various locations on the object surface. This profile can be determined using a machine vision system (also termed herein “vision system”) in the form of a laser displacement sensor (also termed a laser beam “profiler”). A laser displacement sensor captures and determines the (three dimensional) profile of a scanned object surface using a planar curtain formed by optically spreading a laser beam in a “fan” transverse to the beam propagation path. In a conventional arrangement, a vision system camera assembly is oriented to view the plane of the beam from outside the plane. This arrangement captures the profile of the projected line (e.g. extending along the physical x-axis) on the object surface, which, due to the baseline (i.e. the relative spacing along the y-axis) between the beam (fan) plane and the camera causes the imaged line to appear as varying in the image y-axis direction as a function of the physical z-axis height of the imaged point (along the image x-axis). In a typical arrangement the camera optical axis intersects the laser plane at an acute angle and the well-known Scheimpflug configuration of the laser plane, camera lens, and camera image sensor can be used to form an image in which the laser beam deviation is in focus through the region of interest despite the varying distance from the camera. This deviation represents the height profile of the surface. Laser displacement sensors are useful in a wide range of inspection and manufacturing operations where the user desires to measure and characterize surface details of a scanned object via triangulation. One form of laser displacement sensor uses a vision system camera having a lens assembly and image sensor (or “imager”) that can be based upon a CCD or CMOS design. The imager defines a predetermined field of grayscale or color-sensing pixels on an image plane that receives focused light from an imaged scene through a lens.
In a typical arrangement, the displacement sensor and/or object are in relative motion (usually in the physical y-coordinate direction) so that the object surface is scanned by the camera, and a sequence of images are acquired of the laser line at desired spatial intervals—typically in association with an encoder or other motion measurement device (or, alternatively, at time based intervals). Each of these single profile lines is typically derived from a single acquired image of a larger field of view that is known to contain the projected line. These lines collectively describe the surface of the imaged object. The field of view is characterized by a working distance—that is, the surface of the object should reside between a maximum and minimum height to appropriately capture profile information. Within this working distance, the size and shape of the line can vary based upon a variety of factors, including the orientation and reflectivity of the surface being scanned, the varying thickness of the laser plane (the line is typically narrowest at a “waist” at some intermediate depth from the sensor, and wider both closer to and farther from the sensor), and the varying amount of magnification and foreshortening in the camera system as a function of height. This variation in line size/geometry poses one of several challenges in obtaining an accurate measurement of a surface at a desired scanning speed.
In measuring an object surface profile, it is sometimes desirable to simultaneously generate a grayscale image of the object. While such grayscale images can provide a view of the object, the grayscale images may have differing characteristics that can prevent a useful comparison between it and the derived object surface profile. For example, the grayscale image and other images generated may have different pixel scales. In this regard, if an object in physical space is further from a camera, e.g., at a lower height, then a pixel can appear wider and cover more physical space than an object closer to the camera. This effect can cause distortion in the resulting grayscale image and can prevent or make difficult a comparison between the grayscale image and other images generated during the process. It is therefore desirable for the grayscale images to have uniform pixel scales, both within a single grayscale image and among separate grayscale images.
Machine vision applications often require the use of the highest quality imaging components. In recent times, the cost of imaging equipment, such as cameras, has increased. As a result, those in the market may be forced to choose between paying the ever-increasing costs for the highest quality of components or to accept lesser quality imaging equipment at a lower cost. Such lesser quality equipment often includes defects or irregularities that make it less desirable for use in than the use higher quality equipment. The use of such lesser quality equipment can potentially degrade the results of machine vision applications. In particular, sensors can often have one or more bad sensing elements. Bad sensing elements may be “stuck” in that they do not respond significantly to illumination at all, but show an approximately constant value. Other bad sensing elements may respond to illumination, but with one or more parameters of the response, such as offset, gain, nonlinearity, or noise level being significantly different from the nominal response of “good” elements.